journal article·2021-11-25Open access

Comprehensive Assessment of Left Intraventricular Hemodynamics Using a Finite Element Method: An Application to Dilated Cardiomyopathy Patients

Pamela Franco, Julio Sotelo, Cristian Montalba, Bram Ruijsink, Eric Kerfoot, David Nordsletten, Joaquín Mura, Daniel Hurtado, Sergio Uribe

Applied Sciences· Volume 11· Issue 23

Abstract

In this paper, we applied a method for quantifying several left intraventricular hemodynamic parameters from 4D Flow data and its application in a proof-of-concept study in dilated cardiomyopathy (DCM) patients. In total, 12 healthy volunteers and 13 DCM patients under treatment underwent short-axis cine b-SSFP and 4D Flow MRI. Following 3D segmentation of the left ventricular (LV) cavity and registration of both sequences, several hemodynamic parameters were calculated at peak systole, e-wave, and end-diastole using a finite element approach. Sensitivity, inter- and intra-observer reproducibility of hemodynamic parameters were evaluated by analyzing LV segmentation. A local analysis was performed by dividing the LV cavity into 16 regions. We found significant differences between volunteers and patients in velocity, vorticity, viscous dissipation, energy loss, and kinetic energy at peak systole and e-wave. Furthermore, although five patients showed a recovered ejection fraction after treatment, their hemodynamic parameters remained low. We obtained several hemodynamic parameters with high inter- and intra-observer reproducibility. The sensitivity study revealed that hemodynamic parameters showed a higher accuracy when the segmentation underestimates the LV volumes. Our approach was able to identify abnormal flow patterns in DCM patients compared to volunteers and can be applied to any other cardiovascular diseases.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Cardiovascular Function and Risk Factors · Cardiomyopathy and Myosin Studies · Cardiac Valve Diseases and Treatments

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Biomedical Imaging Center, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile

Electrical Engineering Department, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile

Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago 7820436, Chile

School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso 2362905, Chile

Radiology Department, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 833023, Chile

Guy’s and St Thomas’ NHS Foundation Trust, London SE1 7EH, UK

School of Imaging Sciences and Biomedical Engineering, Faculty of Science of Life and Medicine, King’s College London, London WC2R 2LS, UK

Division of Biomedical Engineering and Imaging Sciences, Department of Biomedical Engineering, King’s College London, London WC2R 2LS, UK

Department of Biomedical Engineering and Cardiac Surgery, University of Michigan, North Campus Research Center, Ann Arbor, MI 48109, USA

Department of Mechanical Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile

Structural and Geotechnical Engineering Department, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile

Institute for Biological and Medical Engineering, School of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile

References (41)

Show source-provided references
1. Hershberger, R.E., and Morales, A. (2007, July 27). Dilated Cardiomyopathy Overview. GeneReviews®, Available online: https://www.ncbi.nlm.nih.gov/books/NBK1309/.
2. Mahmaljy, H., Yelamanchili, V.S., and Singhal, M. (2021). Dilated Cardiomyopathy. StatPearls, StatPearls Publishing.
3. Cardiac plasticity10.1056/NEJMra072139 ↗
4. Severity of left ventricular remodeling defines outcomes and response to therapy in heart failure: Valsartan heart failure trial (Val-HeFT) echocardiographic data10.1016/j.jacc.2003.12.053 ↗
5. Dilated Cardiomyopathy: Genetic Determinants and Mechanisms10.1161/CIRCRESAHA.116.309396 ↗
6. Three-dimensional modeling for functional analysis of cardiac images: A review10.1109/42.906421 ↗
8. 4D Flow cardiovascular magnetic resonance consensus statement10.1186/s12968-015-0174-5 ↗
9. Three-dimensional quantification of vorticity and helicity from 3D cine PC-MRI using finite-element interpolations10.1002/mrm.26687 ↗
10. 3D Quantification of Wall Shear Stress and Oscillatory Shear Index Using a Finite-Element Method in 3D CINE PC-MRI Data of the Thoracic Aorta10.1109/TMI.2016.2517406 ↗
11. 3D axial and circumferential wall shear stress from 4D Flow MRI data using a finite element method and a laplacian approach10.1002/mrm.26927 ↗
12. Cardiac flow analysis applied to phase contrast magnetic resonance imaging of the heart10.1007/s10439-009-9709-y ↗
13. Hemodynamic and energetic aspects of the left ventricle in patients with mitral regurgitation before and after mitral valve surgery10.1002/jmri.24926 ↗
14. Svalbring, E., Fredriksson, A., Eriksson, J., Dyverfeldt, P., Ebbers, T., Bolder, A.F., Engvall, J., and Carlhäll, C.-J. (2016). Altered Diastolic Flow Patterns and Kinetic Energy in Subtle Left Ventricular Remodeling and Dysfunction Detected by 4D Flow MRI. PLoS ONE, 11.10.1371/journal.pone.0161391 ↗
15. Turbulent kinetic energy in the right ventricle: Potential MR marker for risk stratification of adults with repaired Tetralogy of Fallot10.1002/jmri.25830 ↗
16. Vortex ring formation in the left ventricle of the heart: Analysis by 4D Flow MRI and Lagrangian coherent structures10.1007/s10439-012-0615-3 ↗
17. Browning, J.R., Hertzberg, J.R., Schroeder, J.D., and Fenster, B.E. (2017). 4D Flow Assessment of Vorticity in Right Ventricular Diastolic Dysfunction. Bioengineering, 4.10.3390/bioengineering4020030 ↗
18. Assessment of intracardiac flow and vorticity in the right heart of patients after repair of tetralogy of Fallot by flow-sensitive 4D MRI10.1007/s00330-015-4186-1 ↗
19. Intra-left ventricular flow dynamics in patients with preserved and impaired left ventricular function: Analysis with 3D cine phase contrast MRI (4D-Flow)10.1002/jmri.25315 ↗
20. Left ventricular fluid kinetic energy time curves in heart failure from cardiovascular magnetic resonance 4D Flow data10.1186/s12968-015-0211-4 ↗
21. Turbulent kinetic energy in normal and myopathic left ventricles10.1002/jmri.24633 ↗
22. Vortex ring behavior provides the epigenetic blueprint for the human heart10.1038/srep22021 ↗
23. The vortex—An early predictor of cardiovascular outcome?10.1038/nrcardio.2014.75 ↗
24. Decreased Diastolic Ventricular Kinetic Energy in Young Patients with Fontan Circulation Demonstrated by Four-Dimensional Cardiac Magnetic Resonance Imaging
25. Quantification of wall shear stress using a finite-element method in multidimensional phase-contrast MR data of the thoracic aorta10.1016/j.jbiomech.2015.04.038 ↗
26. Classification of the cardiomyopathies: A position statement from the European Society Of Cardiology Working Group on Myocardial and Pericardial Diseases10.1093/eurheartj/ehm342 ↗
27. Zheng, G., Liao, H., Jannin, P., Cattin, P., and Lee, S.L. (2016). Visualization and Computational Framework for Multi-modal Biomedical Data Analysis. Medical Imaging and Augmented Reality, MIAR, Springer. Lecture Notes in Computer Science.10.1007/978-3-319-43775-0 ↗
28. Heiberg, E., Sjögren, J., Ugander, M., Carlsson, M., Engblom, H., and Arheden, H. (2010). Design and validation of Segment–freely available software for cardiovascular image analysis. BMC Med. Imaging, 10.10.1186/1471-2342-10-1 ↗
29. Tufvesson, J., Hedstrom, E., Steding-Ehrenborg, K., Carlsson, M., Arheden, H., and Heiberg, E. (2015). Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging. Biomed. Res. Int., 2015.10.1155/2015/970357 ↗
30. Time Resolved Three-dimensional Segmentation of the Left Ventricle10.1109/CIC.2005.1588172 ↗
31. Fang, Q., and Boas, D. (July, January 28). Tetrahedral mesh generation from volumetric binary and gray-scale images. Proceedings of the IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA.
32. Bebis, G. (2010). A Study of Hierarchical Correlation Clustering for Scientific Volume Data. Advances in Visual Computing, Springer. ISVC 2010. Lecture Notes in Computer Science.
33. 4D Flow MRI in bicuspid aortic valve disease demonstrates altered distribution of aortic blood flow helicity10.1002/mrm.24802 ↗
34. Accuracy of out-of-plane vorticity measurements derived from in-plane velocity field data10.1007/s003480050248 ↗
35. Left ventricular reverse remodeling in dilated cardiomyopathy-maintained subclinical myocardial systolic and diastolic dysfunction10.1007/s10554-016-1042-6 ↗
36. Left Ventricular Diastolic Mechanical Dyssynchrony and Associated Clinical Outcomes in Children With Dilated Cardiomyopathy10.1161/CIRCIMAGING.108.782086 ↗
37. Interpretation of Left Ventricular Diastolic Dysfunction in Children With Cardiomyopathy by Echocardiography10.1161/CIRCIMAGING.112.000175 ↗
38. Four-dimensional blood flow-specific markers of LV dysfunction in dilated cardiomyopathy10.1093/ehjci/jes159 ↗
39. Left Ventricular Flow Analysis: Novel Imaging Biomarkers and Predictors of Exercise Capacity in Heart Failure10.1161/CIRCIMAGING.118.008130 ↗
40. Assessment of left ventricular hemodynamic forces in healthy subjects and patients with dilated cardiomyopathy using 4D Flow MRI10.14814/phy2.12685 ↗
41. Segmental Myocardial Velocities in Dilated Cardiomyopathy with and without Left Bundle Branch Block10.1002/jmri.23803 ↗